Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
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Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
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Drugs Recommendation Using ReviewsAnalyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.
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NniAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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Amazon Forest Computer VisionAmazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
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ArticlesA repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci
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LightautomlLAMA - automatic model creation framework
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Dat8General Assembly's 2015 Data Science course in Washington, DC
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Datasist A Python library for easy data analysis, visualization, exploration and modeling
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fastknnFast k-Nearest Neighbors Classifier for Large Datasets
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Ds and ml projectsData Science & Machine Learning projects and tutorials in python from beginner to advanced level.
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DeltapyDeltaPy - Tabular Data Augmentation (by @firmai)
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Machine learningEstudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
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Apartment-Interest-PredictionPredict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.
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NlpythonThis repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
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Machine learning basicsPlain python implementations of basic machine learning algorithms
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Ml Dl ScriptsThe repository provides usefull python scripts for ML and data analysis
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Basketball analyticsRepository which contains various scripts and work with various basketball statistics
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Machine Learning NumpyGathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!
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BlurrData transformations for the ML era
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MachinelearningA repo with tutorials for algorithms from scratch
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ImageclassificationDeep Learning: Image classification, feature visualization and transfer learning with Keras
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VizukaExplore high-dimensional datasets and how your algo handles specific regions.
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SegmentationTensorflow implementation : U-net and FCN with global convolution
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Openml RR package to interface with OpenML
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BtctradingTime Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms
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Dog Breeds ClassificationSet of scripts and data for reproducing dog breed classification model training, analysis, and inference.
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KriskStatistical Interactive Visualization with pandas+Jupyter integration on top of Echarts.
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Kaggle HousepricesKaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-is-pca-lb-0-11421-top-4
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Pythondatarepo for code published on pythondata.com
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Seaborn TutorialThis repository is my attempt to help Data Science aspirants gain necessary Data Visualization skills required to progress in their career. It includes all the types of plot offered by Seaborn, applied on random datasets.
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Ds bowl 2018Kaggle Data Science Bowl 2018
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Unet TgsApplying UNET Model on TGS Salt Identification Challenge hosted on Kaggle
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Learning Vis ToolsLearning Vis Tools: Tutorial materials for Data Visualization course at HKUST
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Ml Fraud DetectionCredit card fraud detection through logistic regression, k-means, and deep learning.
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PbpythonCode, Notebooks and Examples from Practical Business Python
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CleanlabThe standard package for machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.
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Pandas VideosJupyter notebook and datasets from the pandas Q&A video series
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Dive Into Machine LearningDive into Machine Learning with Python Jupyter notebook and scikit-learn! First posted in 2016, maintained as of 2021. Pull requests welcome.
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